SCEBE: an efficient and scalable algorithm for genome-wide association studies on longitudinal outcomes with mixed-effects modeling.

Genome-wide association studies (GWAS) using longitudinal phenotypes collected over time is appealing due to the improvement of power. However, computation burden has been a challenge because of the complex algorithms for modeling the longitudinal data. Approximation methods based on empirical Bayesian estimates (EBEs) from mixed-effects modeling have been developed to expedite the analysis. However, our analysis demonstrated that bias in both association test and estimation for the existing EBE-based methods remains an issue. We propose an incredibly fast and unbiased method (simultaneous correction for EBE, SCEBE) that can correct the bias in the naive EBE approach and provide unbiased P-values and estimates of effect size. Through application to Alzheimer's Disease Neuroimaging Initiative data with 6 414 695 single nucleotide polymorphisms, we demonstrated that SCEBE can efficiently perform large-scale GWAS with longitudinal outcomes, providing nearly 10 000 times improvement of computational efficiency and shortening the computation time from months to minutes. The SCEBE package and the example datasets are available at https://github.com/Myuan2019/SCEBE.

Considerations for pooling real-world data as a comparator cohort to a single arm trial: a simulation study on assessment of heterogeneity.

BACKGROUND: Novel precision medicine therapeutics target increasingly granular, genomically-defined populations. Rare sub-groups make it challenging to study within a clinical trial or single real-world data (RWD) source; therefore, pooling from disparate sources of RWD may be required for feasibility. Heterogeneity assessment for pooled data is particularly complex when contrasting a pooled real-world comparator cohort (rwCC) with a single-arm clinical trial (SAT), because the individual comparisons are not independent as all compare a rwCC to the same SAT. Our objective was to develop a methodological framework for pooling RWD focused on the rwCC use case, and simulate novel approaches of heterogeneity assessment, especially for small datasets. METHODS: We present a framework with the following steps: pre-specification, assessment of dataset eligibility, and outcome analyses (including assessment of outcome heterogeneity). We then simulated heterogeneity assessments for a binary response outcome in a SAT compared to two rwCCs, using standard methods for meta-analysis, and an Adjusted Cochran's Q test, and directly comparing the individual participant data (IPD) from the rwCCs. RESULTS: We found identical power to detect a true difference for the adjusted Cochran's Q test and the IPD method, with both approaches superior to a standard Cochran's Q test. When assessing the impact of heterogeneity in the null scenario of no difference between the SAT and rwCCs, a lack of statistical power led to Type 1 error inflation. Similarly, in the alternative scenario of a true difference between SAT and rwCCs, we found substantial Type 2 error, with underpowered heterogeneity testing leading to underestimation of the treatment effect. CONCLUSIONS: We developed a methodological framework for pooling RWD sources in the context of designing a rwCC for a SAT. When testing for heterogeneity during this process, the adjusted Cochran's Q test matches the statistical power of IPD heterogeneity testing. Limitations of quantitative heterogeneity testing in protecting against Type 1 or Type 2 error indicate these tests are best used descriptively, and after careful selection of datasets based on clinical/data considerations. We hope these findings will facilitate the rigorous pooling of RWD to unlock insights to benefit oncology patients.

Electroanalytical Trace Metal Cations Quantification and Speciation in Freshwaters: Historical Overview, Critical Review of the Last Five Years and Road Map for Developing Dynamic Speciation Field Measurements.

An historical overview covering the field of electroanalytical metal cations speciation in freshwaters is presented here, detailing both the notable experimental and theoretical developments. Then, a critical review of the progress in the last five years is given, underlining in particular the improvements in electrochemical setups and methodologies dedicated to field surveys. Given these recent achievements, a road map to carry out on-site dynamic metal speciation measurements is then proposed, and the key future developments are discussed. This review shows that electroanalytical stripping techniques provide a unique framework for quantitatively assessing metals at trace levels while offering access to both thermodynamic and dynamic features of metal complexation with natural colloidal and particulate ligands.

ISIDORE, a Probe for In Situ Trace Metal Speciation Based on the Donnan Membrane Technique and Electrochemical Detection Part 2: Cd and Pb Measurements during the Accumulation Time of the Donnan Membrane Technique.

The Donnan membrane technique (DMT), in which a synthetic or natural solution (the "donor") is separated from a ligand-free solution (the "acceptor") by a cation-exchange membrane, is a recognized technique for measuring the concentration of a free metal ion in situ, with coupling to electrochemical detection allowing for the quantification of the free metal ion directly on site. However, the use of the DMT requires waiting for the free metal ion equilibrium between the donor and the acceptor solution. In this paper, we investigated the possibility of using the kinetic information and showed that non-equilibrium experimental calibrations of Cd and Pb with the ISIDORE probe could be used to measure free metal concentrations under conditions of membrane-controlled diffusion transport. The application of this dynamic approach made it possible to successfully determine the concentration of free Cd in synthetic and natural river samples. Furthermore, it was found that the determination of free Cd from the slope was not affected by the Ca concentration ratio between the acceptor and donor solution, as opposed to the traditional approach based on Donnan equilibrium. This ISIDORE probe appears to be a promising tool for determining free metal ions in natural samples.

Developing a Compost Quality Index (CQI) Based on the Electrochemical Quantification of Cd (HA) Reactivity.

The present work demonstrates the use of Cd2+ as a reactivity probe of the fulvic acids (FAs), humic acids (HAs) and dissolved organic matter (DOM) compost extracts. Significant differences were observed between the extracts, with the HA extract showing the highest reactivity. Comparing the different composts, the largest reactivity variation was again observed for HA then FA and finally DOM extracts. The Cd2+ binding extent was used to calculate the quality of composts and compared with a reference of uncomposted organic fertiliser (FLW), leading to the definition of an operational scale of compost quality. The parameter equivalent mass of fertiliser (mEF) was used for this scale sorted the seven composts from 0.353 to 1.09 kg FLW, for compost of sewage sludge (CSS) and vermicompost of domestic waste (CVDW), respectively. The significance of this parameter was verified through a correlation analysis between binding extent and the effect of compost application on lettuce crop growth in a field trial. The results demonstrate the potentiality of FA and HA extracts as markers of compost bioactivity and the use of Cd2+ as a reactivity probe.

Breeding for disease resistance in soybean: a global perspective.

KEY MESSAGE: This review provides a comprehensive atlas of QTLs, genes, and alleles conferring resistance to 28 important diseases in all major soybean production regions in the world. Breeding disease-resistant soybean [Glycine max (L.) Merr.] varieties is a common goal for soybean breeding programs to ensure the sustainability and growth of soybean production worldwide. However, due to global climate change, soybean breeders are facing strong challenges to defeat diseases. Marker-assisted selection and genomic selection have been demonstrated to be successful methods in quickly integrating vertical resistance or horizontal resistance into improved soybean varieties, where vertical resistance refers to R genes and major effect QTLs, and horizontal resistance is a combination of major and minor effect genes or QTLs. This review summarized more than 800 resistant loci/alleles and their tightly linked markers for 28 soybean diseases worldwide, caused by nematodes, oomycetes, fungi, bacteria, and viruses. The major breakthroughs in the discovery of disease resistance gene atlas of soybean were also emphasized which include: (1) identification and characterization of vertical resistance genes reside rhg1 and Rhg4 for soybean cyst nematode, and exploration of the underlying regulation mechanisms through copy number variation and (2) map-based cloning and characterization of Rps11 conferring resistance to 80% isolates of Phytophthora sojae across the USA. In this review, we also highlight the validated QTLs in overlapping genomic regions from at least two studies and applied a consistent naming nomenclature for these QTLs. Our review provides a comprehensive summary of important resistant genes/QTLs and can be used as a toolbox for soybean improvement. Finally, the summarized genetic knowledge sheds light on future directions of accelerated soybean breeding and translational genomics studies.

Absolute and Relative Positioning of Natural Organic Matter Acid-Base Potentiometric Titration Curves: Implications for the Evaluation of the Density of Charged Reactive Sites.

Potentiometric acid-base titration curves collected on humic (nano)particles as a function of pH and salt concentration reflect the electrostatics of the particles and the amount of chemical charges (Q) they carry. In turn, the interpretation of titration data helps quantify their reactivity toward metals provided that both intrinsic chemical and nonspecific electrostatic contributions to proton binding are correctly unraveled. Establishing a titration curve requires several steps, i.e., blank subtraction, relative curve positioning with respect to the electrolyte concentration, and absolute curve positioning achieved by the estimation of particle charge Q0 at low pH. Failure to properly establish each step may lead to the misevaluation of nanoparticle charging behavior. Here, we report (i) a simple procedure to measure and position titration curves for humic substances (HS) versus salt concentration and (ii) an original approach for absolute curve positioning upon the exploitation of proton affinity spectra. The latter do not depend on Q0 and they thus constrain the titration data analysis using the soft Poisson-Boltzmann-based titration (SPBT) formalism for nanoparticles in the thick electric double-layer regime. We illustrate the benefits of our approach by analyzing titration measurements for a large range of humic nanoparticles and by comparing the outcome with results from the literature.

High-throughput and efficient multilocus genome-wide association study on longitudinal outcomes.

MOTIVATION: With the emerging of high-dimensional genomic data, genetic analysis such as genome-wide association studies (GWAS) have played an important role in identifying disease-related genetic variants and novel treatments. Complex longitudinal phenotypes are commonly collected in medical studies. However, since limited analytical approaches are available for longitudinal traits, these data are often underutilized. In this article, we develop a high-throughput machine learning approach for multilocus GWAS using longitudinal traits by coupling Empirical Bayesian Estimates from mixed-effects modeling with a novel ℓ0-norm algorithm. RESULTS: Extensive simulations demonstrated that the proposed approach not only provided accurate selection of single nucleotide polymorphisms (SNPs) with comparable or higher power but also robust control of false positives. More importantly, this novel approach is highly scalable and could be approximately >1000 times faster than recently published approaches, making genome-wide multilocus analysis of longitudinal traits possible. In addition, our proposed approach can simultaneously analyze millions of SNPs if the computer memory allows, thereby potentially allowing a true multilocus analysis for high-dimensional genomic data. With application to the data from Alzheimer's Disease Neuroimaging Initiative, we confirmed that our approach can identify well-known SNPs associated with AD and were much faster than recently published approaches (≥6000 times). AVAILABILITY AND IMPLEMENTATION: The source code and the testing datasets are available at https://github.com/Myuan2019/EBE_APML0. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Developing On-Site Trace Level Speciation of Lead, Cadmium and Zinc by Stripping Chronopotentiometry (SCP): Fast Screening and Quantification of Total Metal Concentrations.

Electrochemical stripping techniques are interesting candidates for carrying out onsite speciation of environmentally relevant trace metals due to the existing low-cost portable instrumentation available and the low detection limits that can be achieved. In this work, we describe the initial analytical technique method development by quantifying the total metal concentrations using Stripping Chronopotentiometry (SCP). Carbon paste screen-printed electrodes were modified with thin films of mercury and used to quantify sub-nanomolar concentrations of lead and cadmium and sub-micromolar concentrations of zinc in river water. Low detection limits of 0.06 nM for Pb(II) and 0.04 nM for Cd(II) were obtained by the standard addition method using a SCP deposition time of 180 s. The SCP results obtained for Pb(II) and Cd(II) agreed with those of inductively coupled plasma mass spectrometry (ICP-MS). The coupling of SCP with screen-printed electrodes opens up excellent potential for the development of onsite speciation of trace metals. Due to the low analysis throughput obtained for the standard addition method, we also propose a new, more rapid screening Cd(II) internal standard methodology to significantly increase the number of samples that can be analyzed per day.

A novel quantification of information for longitudinal data analyzed by mixed-effects modeling.

Nonlinear mixed-effects (NLME) modeling is one of the most powerful tools for analyzing longitudinal data especially under the sparse sampling design. The determinant of the Fisher information matrix is a commonly used global metric of the information that can be provided by the data under a given model. However, in clinical studies, it is also important to measure how much information the data provide for a certain parameter of interest under the assumed model, for example, the clearance in population pharmacokinetic models. This paper proposes a new, easy-to-interpret information metric, the "relative information" (RI), which is designed for specific parameters of a model and takes a value between 0% and 100%. We establish the relationship between interindividual variability for a specific parameter and the variance of the associated parameter estimator, demonstrating that, under a "perfect" experiment (eg, infinite samples or/and minimum experimental error), the RI and the variance of the model parameter estimator converge, respectively, to 100% and the ratio of the interindividual variability for that parameter and the number of subjects. Extensive simulation experiments and analyses of three real datasets show that our proposed RI metric can accurately characterize the information for parameters of interest for NLME models. The new information metric can be readily used to facilitate study designs and model diagnosis.

Polymer-Decorated Cellulose Nanocrystals as Environmentally Friendly Additives for Olefin-Based Drilling Fluids.

In this study, we intended to evaluate the performance of olefin-based drilling fluids after addition of cellulose nanocrystal (CNC) derivatives. For this purpose, firstly, cellulose nanocrystals, produced from sulfuric acid hydrolysis of cotton fibers, were functionalized with poly(N-isopropylacrylamide) (PNIPAM) chains via free radicals. The samples were then characterized via Fourier transform infrared spectroscopy (FTIR), nuclear magnetic resonance (NMR), X-ray diffraction (XRD), thermogravimetric analysis (TGA), confocal microscopy, dynamic light scattering (DLS), and zeta potential measurements in water. The FTIR and NMR spectra exhibited the characteristic signals of CNC and PNIPAM groups, indicating successful grafting. As expected, X-ray diffractograms showed that the crystallinity of CNCs reduces after chemical modification. TGA revealed that the surface-functionalized CNCs present higher thermal stability than pure CNCs. The confocal microscopy, zeta potential, and DLS results were consistent with the behavior of cellulose nanocrystals decorated by a shell of PNIPAM chains. The fluids with a small amount of modified CNCs presented a much lower volume of filtrate after high-temperature and high-pressure (HTHP) filtration tests than the corresponding standard fluid, indicating the applicability of the environmentally friendly particles for olefin-based drilling fluids.

Evaluation of a rapid diagnostic test for the detection of Streptococcus pyogenes in invasive infections.

Invasive Streptococcus pyogenes diseases represent the most severe form of infection produced by this microorganism. Early diagnosis and treatment are important, due to its potential severity. Etiological confirmation of invasive infection is performed by culture, which takes between 18 and 48h. We tested a rapid immunochromatographic assay directly from clinical samples from normally sterile sites and positive blood culture bottles when positive cocci chains were observed by Gram staining. Eighty samples were analyzed. The rapid test was positive in 35 samples: in 34 of them S. pyogenes was confirmed by culture. The immunochromatographic method showed 97.1% sensitivity and 97.8% specificity. The strept A® immunochromatographic rapid test allows to obtain reliable results in less than 10min and is accessible to any microbiology laboratory. This study demonstrates the potential use of a rapid immunochromatographic method directly from clinical samples and positive blood cultures.

Patterns of nuclear and chloroplast genetic diversity and structure of manioc along major Brazilian Amazonian rivers.

Background and Aims: Amazonia is a major world centre of plant domestication, but little is known about how the crops were dispersed across the region. Manioc (Manihot esculenta) was domesticated in the south-western Amazon basin, and is the most important staple food crop that originated in Amazonia. Current contrasting distributions may reflect distinct histories of dispersal of bitter and sweet manioc landraces. To produce new insights into the evolutionary history of the crop, we investigated the contemporary genetic diversity and structure of bitter and sweet manioc along major Amazonian rivers. Methods: The patterns of genetic structure and diversity of wild and cultivated sweet and bitter manioc with four chloroplast and 14 nuclear microsatellite markers were evaluated. Results were interpreted in terms of the crop's dispersal. Key results: No phylogeographic patterns among rivers were detected, and genetic structure among rivers was confounded by the bitter-sweet divergence. However, differences in the distribution of nuclear diversity and somewhat distinctive patterns of genetic structure across rivers were observed within bitter and sweet manioc. Conclusions: Various pre-Columbian and post-European conquest events in the history of Amazonian occupation may explain the absence of clearer patterns of genetic structure. However, the wide distribution of the most common chloroplast haplotype agrees with an early dispersal of manioc across Brazilian Amazonia. Furthermore, differences in genetic structure and in the spatial distribution of genetic diversity suggest that bitter and sweet manioc had distinct dispersal histories. Knowledge about how prehistoric and contemporary Amazonian peoples manage their crops is valuable for the maintenance and conservation of the impressive diversity of their native crops.

Full covariate modelling approach in population pharmacokinetics: understanding the underlying hypothesis tests and implications of multiplicity.

AIMS: To clarify the hypothesis tests associated with the full covariate modelling (FCM) approach in population pharmacokinetic analysis, investigate the potential impact of multiplicity in population pharmacokinetic analysis, and evaluate simultaneous confidence intervals (SCI) as an approach to control multiplicity. METHODS: Clinical trial simulations were performed using a simple one-compartment pharmacokinetic model. Different numbers of covariates, sample sizes, effect sizes of covariates, and correlations among covariates were explored. The false positive rate (FPR) and power were evaluated. RESULTS: The FPR for the FCM approach dramatically increases with number of covariates. The chance of incorrectly selecting ≥1 seemingly clinically relevant covariates can be increased from 5% to a 40-70% range for 10-20 covariates. The SCI approach may provide appropriate control of the family-wise FPR, allowing more appropriate decision making. As a result, the power detecting real effects without incorrectly identifying non-existing effects can be greatly improved by the SCI approach compared to the approach in current practice. The performance of the SCI approach is driven by the ratio of sample size to number of covariates. The FPR can be controlled at 5% and 10% using the SCI approach when the ratio was ≥20 and 10, respectively. CONCLUSION: The FCM approach still lies within the framework of statistical testing, and therefore multiplicity is an issue for this approach. It is imperative to consider multiplicity reporting and adjustments in FCM modelling practice to ensure more appropriate decision making.

Mating System and Effective Population Size of the Overexploited Neotropical Tree (Myroxylon peruiferum L.f.) and Their Impact on Seedling Production.

The reproductive system of a tree species has substantial impact on genetic diversity and structure within and among natural populations. Such information, should be considered when planning tree planting for forest restoration. Here, we describe the mating system and genetic diversity of an overexploited Neotropical tree, Myroxylon peruiferum L.f. (Fabaceae) sampled from a forest remnant (10 seed trees and 200 seeds) and assess whether the effective population size of nursery-grown seedlings (148 seedlings) is sufficient to prevent inbreeding depression in reintroduced populations. Genetic analyses were performed based on 8 microsatellite loci. M. peruiferum presented a mixed mating system with evidence of biparental inbreeding (t^m-t/ = 0.118). We found low levels of genetic diversity for M. peruiferum species (allelic richness: 1.40 to 4.82; expected heterozygosity: 0.29 to 0.52). Based on Ne(v) within progeny, we suggest a sample size of 47 seed trees to achieve an effective population size of 100. The effective population sizes for the nursery-grown seedlings were much smaller Ne = 27.54-34.86) than that recommended for short term Ne ≥ 100) population conservation. Therefore, to obtain a reasonable genetic representation of native tree species and prevent problems associated with inbreeding depression, seedling production for restoration purposes may require a much larger sampling effort than is currently used, a problem that is further complicated by species with a mixed mating system. This study emphasizes the need to integrate species reproductive biology into seedling production programs and connect conservation genetics with ecological restoration.

Chemodynamics of Soft Nanoparticulate Metal Complexes: From the Local Particle/Medium Interface to a Macroscopic Sensor Surface.

The lability of a complex species between a metal ion M and a binding site S, MS, is conventionally defined with respect to an ongoing process at a reactive interface, for example, the conversion or accumulation of the free metal ion M by a sensor. In the case of soft charged multisite nanoparticulate complexes, the chemodynamic features that are operative within the micro environment of the particle body generally differ substantially from those for dissolved similar single-site complexes in the same medium. Here we develop a conceptual framework for the chemodynamics and the ensuing lability of soft (3D) nanoparticulate metal complexes. The approach considers the dynamic features of MS at the intraparticulate level and their impact on the overall reactivity of free metal ions at the surface of a macroscopic sensing interface. Chemodynamics at the intraparticulate level is shown to involve a local reaction layer at the particle/medium interface, while at the macroscopic sensor level an operational reaction layer is invoked. Under a certain window of conditions, volume exclusion of the nanoparticle body near the medium/sensor interface is substantial and affects the properties of the reaction layer and the overall lability of the nanoparticulate MS complex toward the reactive surface.

Dynamic population pharmacokinetic-pharmacodynamic modelling and simulation supports similar efficacy in glycosylated haemoglobin response with once or twice-daily dosing of canagliflozin.

AIM: Canagliflozin is an SGLT2 inhibitor approved for the treatment of type-2 diabetes. A dynamic population pharmacokinetic-pharmacodynamic (PK/PD) model relating 24-h canagliflozin exposure profiles to effects on glycosylated haemoglobin was developed to compare the efficacy of once-daily and twice-daily dosing. METHODS: Data from two clinical studies, one with once-daily, and the other with twice-daily dosing of canagliflozin as add-on to metformin were used (n = 1347). An established population PK model was used to predict full 24-h profiles from measured trough concentrations and/or baseline covariates. The dynamic PK/PD model incorporated an Emax relationship between 24-h canagliflozin exposure and HbA1c-lowering with baseline HbA1c affecting the efficacy. RESULTS: Internal and external model validation demonstrated that the model adequately predicted HbA1c-lowering for canagliflozin once-daily and twice-daily dosing regimens. The differences in HbA1c reduction between the twice-daily and daily mean profiles were minimal (at most 0.023% for 100 mg total daily dose [TDD] and 0.011% for 300 mg TDD, up to week 26, increasing with time and decreasing with TDD) and not considered clinically meaningful. CONCLUSIONS: Simulations using this model demonstrated the absence of clinically meaningful between-regimen differences in efficacy, supported the regulatory approval of a canagliflozin-metformin immediate release fixed-dose combination tablet and alleviated the need for an additional clinical study.

Impact of intracellular metallothionein on metal biouptake and partitioning dynamics at bacterial interfaces.

Genetically engineered microorganisms are alternatives to physicochemical methods for remediation of metal-contaminated aquifers due to their remarkable bioaccumulation capacities. The design of such biosystems would benefit from the elaboration of a sound quantitative connection between performance in terms of metal removal from aqueous solution and dynamics of the multiscale processes leading to metal biouptake. In this work, this elaboration is reported for Escherichia coli cells modified to overexpress intracellular metallothionein (MTc), a strong proteinaceous metal chelator. Depletion kinetics of Cd(ii) from bulk solution following biouptake and intracellular accumulation is addressed as a function of cell volume fraction using electroanalytical probes and ligand exchange-based analyses. It is shown that metal biouptake in the absence and presence of MTc is successfully interpreted on the basis of a formalism recently developed for metal partitioning dynamics at biointerfaces with integration of intracellular metal speciation. The analysis demonstrates how fast sequestration of metals by intracellular MTc bypasses metal excretion (efflux) and enhances the rate of metal depletion to an extent such that complete removal is achieved at sufficiently large cell volume fractions. The magnitude of the stability constant of nanoparticulate metal-MTc complexes, as derived from refined analysis of macroscopic bulk metal depletion data, is further confirmed by independent electrochemical measurement of metal binding by purified MTc extracts.

Circulating levels of pentraxin-3 (PTX3) in patients with liver cirrhosis.

BACKGROUND: Despite the circulating levels of PTX3 were related to the severity of various diseases, there are no studies investigating its role in patients with liver cirrhosis. We aimed to study PTX3 levels in patients with liver cirrhosis. MATERIAL AND METHODS: A prospective cohort study included 130 patients hospitalized for acute decompensation of liver cirrhosis, 29 stable cirrhotic outpatients and 32 healthy controls evaluated in a tertiary hospital in Southern Brasil. RESULTS: The median PTX3 level was significantly higher in stable cirrhotic patients compared to controls (2.6 vs. 1.1 ng/mL; p < 0.001), hospitalized cirrhotic patients compared to controls (3.8 vs. 1.1 ng/mL; p < 0.001), and hospitalized cirrhotic patients compared to stable cirrhotic patients (3.8 vs. 2.6 ng/mL; p = 0.001). A positive correlation was found between PTX3 and serum creatinine (r = 0.220; p = 0.012), Chronic Liver Failure - Sequential Organ Failure Assessment score (CLIF-SOFA) (r = 0.220; p = 0.010), MELD (r = 0.279; p = 0.001) and Child-Pugh score (r = 0.224; p = 0.010). Significantly higher levels of PTX3 were observed in patients on admission with ACLF (8.9 vs. 3.1 ng/mL; p < 0.001) and MELD score ≥ 20 (6.6 vs. 3.4 ng/mL; p = 0.002). Death within 90 days occurred in 30.8% of patients and was associated with higher levels of PTX3 (5.3 vs. 3.4 ng/mL; p = 0.009). The probability of Kaplan-Meier survival was 77.0% in patients with PTX-3 < 5.3 ng mL (upper tercile) and 53.5% in those with PTX3 ≥ 5.3 ng/mL (p = 0.002). CONCLUSION: These results indicate the potential for use of PTX3 as an inflammatory biomarker for the prognosis of patients with hepatic cirrhosis.